3 How To Deal with Partial Disk Writes? Guaranteeing Atomicity Partial disk writes: database writes disk page which consists of several sectors e.g., 8kB page consists of 16 sectors (512B each) power failure during write: page may be only partially written leads to inconsistent database state Disk controller: battery backed cache data in cache is written at restart after power outage consistent state is restored Operating system: file system file system that prevents partial writes, e.g., Raiser 4 Database: e.g., full page writes in PostgreSQL before-image of page is stored before updating it recovery: partially written page is restored and update is repeated 1. Before images: state at transaction start used to undo the effects of a uncommitted transaction before image must remain on stable storage until commit 2. After images: state at transaction end used to install effects of transaction after commit after image must be written to stable storage before commit Johann Gamper (IDSE) Database Management and Tuning Unit 11 9 / 32 Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Concepts Write-Ahead Logging Data files: tables, indexes Log file: stores before and after images Database buffer: contains pages that transactions modify Dirty page: buffer page with uncommitted changes WAL commit: write after images to log file before transaction commits data files can be updated later (after commit) WAL abort: variant 1: explicitly store before image in log variant 2: use data file as a before image only in variant 1 it is safe to write dirty pages to the data file dirty pages are typically written when the database buffer is full Example: WAL for a transaction T that modifies pages P i and P j pages P i and P j are loaded to the database buffer transaction T modifies the pages P i and P j database generates log records lr i and lr j for the modifications database writes log records to stable storage before committing modified pages are written to data file after transaction T commits Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Johann Gamper (IDSE) Database Management and Tuning Unit / 32

6 Experiment Separate Disk for Log 2. Group Commit 300k inserts or update statements. Each statement is a separate transaction and forces a write. Same disk: data files and log are on the same disk. Different disks: log has its own disk. Log buffer is flushed to disk before each commit. Group commit: commit a group of transactions together only one disk write (flush) for all transactions Advantage: higher throughput Disadvantages: some transactions must wait before committing locks are held longer (until commit) lower response time for waiting transactions Oracle 9i on Linux server with internal hard drives (no RAID controller) Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Group Commit Experiment Johann Gamper (IDSE) Database Management and Tuning Unit / 32 WAL Buffer and Group Commit in PostgreSQL Throughput (tuples/sec) Size of Group Commit Increasing the group commit size increases the throughput. DB2 UDB V7.1 on Windows 2000 WAL buffer: Write ahead log buffer RAM buffer, size 64kB=8pages (wal buffers) all log records are written to this buffer WAL page is flushed at commit or every 200ms (wal writer delay) data is written to a file called WAL segment commit delay: (default: 0) time delay between a commit and flushing WAL buffer during waiting period, hopefully other transactions commit if other transaction commits, do group commit if no other transaction commits, waiting time is lost commit sibling: (default: 5) minimum number of concurrent open transactions for group commit if less transactions are open, commit delay is disabled Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Johann Gamper (IDSE) Database Management and Tuning Unit / 32

7 3. WAL Tuning: Trading in Durability (PostgreSQL) 4. Tuning Data Writes synchronous commit: (default: on) call fsync to force operating system to flush disk buffer commit only after fsync returns switch off if you do not want to wait for fsync parameter can be set for each transaction individually Switching off synchronous commit increases performance. Worst case: database consistency not in danger system crash may cause loss of most recently committed transactions lost transactions seem uncommitted to database and are cleanly aborted at startup, resulting in consistent database state client thinks that transaction committed, but it was aborted maximum delay between commit and flush (risk period): 3 wal writer delay (= 3 200ms by default) fsync: (default: on) switching off fsync might result in unrecoverable data corruption synchronous commit: similar performance, less risk At commit time database buffer (in RAM) has committed information log (on disk) has committed information data file may not have committed information Why is data not immediately written to data file? each page write requires a seek resulting random I/O bad for performance Convenient writes: wait and write larger chunks at once write when cheap, e.g., disk heads are on the right cylinder Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Database Writes Tuning Options Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Checkpoint Tuning in PostgreSQL Fill ratio of the database buffer (RAM): Oracle: DB BLOCK MAX DIRTY TARGET specifies maximum number of dirty pages in database buffer SQL Server: pages in free lists falls below threshold (3% by default) Checkpoint frequency: checkpoint forces all committed writes that are only in database buffer or log to the data file less frequent checkpoints allow more convenient writes less frequent checkpoints increase recovery time Checkpoints have a cost: disk activity to transfer dirty pages to data file if full page writes is on (avoid partial disk writes), after checkpoint a before image must be stored in log for each new page that is modified Checkpoint is triggered if one of the following is reached: checkpoint timeout (5min): max interval between checkpoints checkpoint segments (3): max number of log file segments (16MB) Johann Gamper (IDSE) Database Management and Tuning Unit / 32 Johann Gamper (IDSE) Database Management and Tuning Unit / 32

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